mistralai/Mistral-Small-24B-Instruct-2501
Mistral-Small-24B-Instruct-2501 is a 24 billion parameter instruction-fine-tuned large language model developed by Mistral AI. It offers state-of-the-art conversational and reasoning capabilities, comparable to larger models, and features native function calling and JSON outputting. This model is designed for fast response conversational agents, low-latency function calling, and local inference, fitting on a single RTX 4090 or a 32GB RAM MacBook when quantized.
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Hugging Face Popular Sampler Settings
Most commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
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top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.